PhD Studentship
Applied Time Series Methods for Coastal Development
University of Plymouth
The Faculty of Technology
Applications are invited for a three year studentship in Statistics for Time Series Methods for Costal Development, support by the Faculty of Technology scholarships.
These scholarships are for UK/EU fees only. Candidates from overseas will have to find the difference in fees of approximately £5,500.
Some candidates may qualify for a limited maintenance stipend.
Opportunities also exist for students to be employed on a part time basis. Part-time lecturing may also be available.
The successful applicant should have a good honours degree in statistics, mathematics, coastal engineering or an appropriate discipline.
CLOSING DATE FOR APPLICATIONS: TUESDAY 31 MAY 2005.
PLEASE CONTACT MRS C WATSON, RESEARCH ADMINISTRATOR, FACULTY OF TECHNOLOGY, EMAIL [log in to unmask] <[log in to unmask]" target="_blank">http:[log in to unmask]> OR TELEPHONE 01752 233329 FOR AN APPLICATION PACK.
Background to the project
An important issue in coastal development is to look 30, 40 or 50 years ahead when making predictions about shoreline evolution. We also need to consider the variability during this time caused by a string of particularly stormy episodes, for example, or by long-term trends such as sea level rise. Time series methods are essential for this because available data are recorded over time. In this project we will develop new time series methods and associated computational algorithms to make forecasts about shoreline evolution. We will compare these methods to existing approaches, and we will develop reliable, user-friendly software and documentation to allow practitioners to utilize our methodology. This software will be an important output from the project as it will be of interest to engineers for its applicability to coastal development and to statisticians for its theoretical innovation.
Much research into related statistical methodology and applications has recently been carried out by Drs Yuzhi Cai and Julian Stander in the School of Mathematics and Statistics. And these methods have potentially stimulated novel research in costal development. Professor Dominic Reeve has published widely on the use of statistical techniques for predicting coastal change.
For informal enquiries please contact Dr Yuzhi Cai ([log in to unmask]), Dr Julian Stander ([log in to unmask]), and Professor Dominic Reeve ([log in to unmask]).
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